Klaus Frieler

Absolute memory for pitch: A comparative replication of Levitin’s 1994 study in six European labs

In a widely cited study, Levitin (1994) suggested the existence of absolute pitch memory for music in the general population beyond the rare trait of genuine absolute pitch (AP). In his sample, a significant proportion of non-AP possessors were able to reproduce absolute pitch levels when asked to sing very familiar pop songs from memory. Forty-four percent of participants sang the correct pitch on at least one of two trials, and 12% were correct on both trials. However, until now, no replication of this study has ever been published. The current paper presents the results of a large replication endeavour across six different labs in Germany and the UK. All labs used the same methodology, carefully replicating Levitin’s original experiment. In each lab, between 40 and 50 participants were tested (N = 277). Participants were asked to sing two different pop songs of their choice. All sung productions were compared to the original songs. Twenty-five percent of the participants sang the exact pitch of at least one of the two chosen songs and 4% hit the right pitches for both songs. Our results generally confirm the findings of Levitin (1994). However, the results differ considerably across laboratories, and the estimated overall effect using meta-analysis techniques was significantly smaller than Levitin’s original result. This illustrates the variability of empirical findings derived from small sample sizes and corroborates the need for replication and meta-analytical studies in music psychology in general.

Modelling experts notions of melodic similarity

In this article we show that a subgroup of music experts has a reliable and consistent notion of melodic similarity, and that this notion can be measured with satisfactory precision. Our measurements enable us to model the similarity ratings of music experts by automated and algorithmic means. A large number of algorithmic similarity measure found in the literature were mathematically systematised and implemented. The best similarity algorithms compared to human experts were chosen and optimised by statistical means according to different contexts. A multidimensional scaling model of the algorithmic similarity measures is constructed to give an overiew over the different musical dimensions reflected by these measures. We show some examples where this optimised methods could be successfully applied to real world problems like folk song categorisation and analysis, and discuss further applications and implications.

Replication in music psychology

In this article, we address the current state and general role of replication in empirical sciences in general and music psychology in particular. We argue that replication should be an integral part of the quality management of science because it helps to improve and maintain the general benefit of empirical sciences by enhancing the confidence in scientific phenomena and theories. Replicating empirical experiments has two major benefits: (1) It increases the sheer number of observations and (2) it provides independent evidence which works as a safety net against methodological fallacies, causally influential but unknown (i.e., random) factors, researcher degrees of freedom, and outright fraud. Furthermore, we argue that for low-gain/low-cost sciences such as music psychology, measures to ensure quality standards, in particular the amount of replication experiments conducted, can be expected to be lower than in high gain/high cost sciences. These lower expectations stem from the general acknowledgments that in low-gain/low-cost sciences (1) research resources are normally scarce and (2) the consequences of inadequate theories are relatively harmless. We argue that the view of music psychology as a low-cost/low-gain science can explain the striking lack of replication studies and meta-analyses. We also discuss possible counter-measures to enhance the reliability of music-psychological knowledge.

Midlevel analysis of monophonic jazz solos: A new approach to the study of improvisation

We present a novel approach to the analysis of jazz solos based on the categorisation and annotation of musical units on a middle level between single notes and larger form parts. A guideline during development was the hypothesis that these midlevel units (MLU) correspond to the improvising musicians’ playing ideas and action plans. A system of categories was devised, comprising nine main categories (line, lick, theme, quote, melody, rhythm, expressive, fragment, void), 19 subcategories, and 41 sub-subcategories as well as syntactical rules to encode motivic relationships between units. A set of 140 monophonic jazz solos from various jazz styles (traditional, swing, bebop, hardbop, cool jazz, postbop, free jazz) was annotated manually, resulting in 4939 units in total. The median number of midlevel units is 32 per solo and 13.75 per chorus. The average duration is 2.25 s (SD = 1.57 s), in good agreement with the duration of the subjective present. Overall, the most common main category is lick (45.7% of all units), followed by line (31.5%), but distributions of the main MLU types differ significantly between styles and performers. About one quarter (M = 25.1%, SD = 15.3%) of the annotated units have motivic relations to preceding units. The mean length of consecutive motivic chains is 2.8 (SD = 1.4). The amount of motivic relations varies considerably between performers, but not between styles. Based on these first results, we discuss implications for jazz research and options for further applications of the proposed method.

Is Independent Creation Likely to Happen in Pop Music

In this study we try to address the question of whether independent (re-)creations are likely to happen in pop music. The interest in this topic stems from the fact that the claim of an “independent creation” is a common defence strategy in copyright infringement lawsuits. We conducted a main experiment in which subjects were asked to invent short, “catchy” pop melodies to a given backing track over a very common chord sequence (I VI IV V). Additionally, we incorporated 5 melodies from hit songs over the same chords in a comparable tempo. The collected melodies were examined for similarities, between participants’ melodies and hit songs on the one hand, and between participants’ songs on the other. In each case at least two melody pairs with high similarity were found. A deeper analysis of these cases revealed that indeed independent (re-)creations might have taken place.

Evaluating Different Approaches to Measuring the Similarity of Melodies

This paper describes an empirical approach to evaluating similarity measures for the comparision of two note sequences or melodies. In the first sections the experimental approach and the empirical results of previous studies on melodic similarity are reported. In the discussion section several questions are raised that concern the nature of similarity or distance measures for melodies and musical material in general. The approach taken here is based on an empirical comparision of a variety of similarity measures with experimentally gathered rating data from human music experts. An optimal measure is constructed on the basis of a linear model.

Score-Informed Analysis of Tuning, Intonation, Pitch Modulation, and Dynamics in Jazz Solos

Both the collection and analysis of large music repertoires constitute major challenges within musicological disciplines such as jazz research. Automatic methods of music analysis based on audio signal processing have the potential to assist researchers and to accelerate the transcription and analysis of music recordings significantly. In this paper, we propose a framework for analyzing improvised monophonic solos in multi-instrumental jazz recordings with special focus on reed and brass instruments. The analysis algorithms rely on prior score-information, which is taken from high quality manual solo transcriptions. Following an initial solo and accompaniment source separation, we propose algorithms for tone-wise extraction of fundamental frequency and intensity contours. Based on this fine-grained representation of recorded jazz solos, we perform several exploratory experiments motivated by questions relating to jazz research in order to analyze the use of expressive stylistic devices such as intonation, pitch modulation, and dynamics in jazz solos. The results show that a score-informed audio analysis of jazz recordings can provide valuable insights into the individual stylistic characteristics of jazz musicians.

Generalized N-gram Measures for Melodic Similarity

In this paper we propose three generalizations of well-known N-gram approaches for measuring similarity of single-line melodies. In a former paper we compared around 50 similarity measures for melodies with empirical data from music psychological experiments. Similarity measures based on edit distances and N-grams always showed the best results for different contexts. This paper aims at a generalization of N-gram measures that can combine N-gram and other similarity measures in a fairly general way.

Bridging the Gap: Enriching YouTube Videos with Jazz Music Annotations

Web services allow permanent access to music from all over the world. Especially in the case of web services with user-supplied content, e.g., YouTube(TM), the available metadata is often incomplete or erroneous. On the other hand, a vast amount of high-quality and musically relevant metadata has been annotated in research areas such as Music Information Retrieval (MIR). Although they have great potential, these musical annotations are ofter inaccessible to users outside the academic world. With our contribution, we want to bridge this gap by enriching publicly available multimedia content with musical annotations available in research corpora, while maintaining easy access to the underlying data. Our web-based tools offer researchers and music lovers novel possibilities to interact with and navigate through the content. In this paper, we consider a research corpus called the Weimar Jazz Database (WJD) as an illustrating example scenario. The WJD contains various annotations related to famous jazz solos. First, we establish a link between the WJD annotations and corresponding YouTube videos employing existing retrieval techniques. With these techniques, we were able to identify 988 corresponding YouTube videos for 329 solos out of 456 solos contained in the WJD. We then embed the retrieved videos in a recently developed web-based platform and enrich the videos with solo transcriptions that are part of the WJD. Furthermore, we integrate publicly available data resources from the Semantic Web in order to extend the presented information, for example, with a detailed discography or artists-related information. Our contribution illustrates the potential of modern web-based technologies for the digital humanities, and novel ways for improving access and interaction with digitized multimedia content.